Kuttel, Michelle and Ravenscroft, Neil (2018) The Role of Molecular Modeling in Predicting Carbohydrate Antigen Conformation and Understanding Vaccine Immunogenicity., Carbohydrate-Based Vaccines: From Concept to Clinic. ACS Symposium Series, Vol. 1290., 139-173, American Chemical Society.
Full text not available from this repository. (Use alternate locations listed below)Abstract
Licensed conjugate vaccines have proven to be highly effective in preventing bacterial disease. Coverage of a vaccine is extended when specific antigens elicit immune responses that provide cross-protection against infection by closely related, non-vaccine strains. However, structural similarity between carbohydrate antigens has not proven to be a reliable predictor of cross-protection and the current understanding of the role of saccharide antigen conformation in immunogenicity is sparse. Identification of the conformational effect of specific structural changes in conjugate vaccine antigens may usefully inform the development of conjugate vaccines. The limited ability of experimental methods to establish saccharide conformation has led to the development of systematic molecular modeling protocols. Here we cover the computational methodologies employed to model carbohydrate antigens and demonstrate, through case studies, the valuable role that molecular simulations can play in furthering our understanding of carbohydrate immunogenicity. The case studies comprise molecular modeling of the capsular polysaccharides for meningococcal serogroups Y and W and pneumococcal serogroups 6, 19 and 23, as well O-antigens of Salmonella enterica and Shigella flexneri. Conformational analysis can provide a mechanistic insight into clinical observations on cross-protection and may further indicate the importance of specific structural features, such as substituents, thereby facilitating vaccine design and broadening vaccine coverage.
| Item Type: | Book chapter |
|---|---|
| Additional Information: | DOI:10.1021/bk-2018-1290.ch007 |
| Uncontrolled Keywords: | conjugate vaccines, molecular modelling, glycoinformatics, |
| Subjects: | Applied computing > Life and medical sciences Computing methodologies > Modeling and simulation |
| Date Deposited: | 09 Nov 2018 |
| Last Modified: | 10 Oct 2019 15:31 |
| URI: | http://pubs.cs.uct.ac.za/id/eprint/1264 |
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